importance.combinedGradientForest: Importance of predictors or species for a...

In gradientForest: Random Forest functions for the Census of Marine Life synthesis project.

Importance of predictors or species for a combinedGradientForest object

Description

Provide access to the importance values of predictors or species

Usage

## S3 method for class 'combinedGradientForest'
importance(x, type = c("Weighted", "Raw", "Species")[1], sort = TRUE, ...)

Arguments

x	an object of class combinedGradientForest generated by combinedGradientForest.
type	type of importance measure. The choices are Weighted: measure is an average of accuracy importance weighted by species R^2 Raw: measure is a simple average of accuracy importance over species Species: measure is the species R^2
sort	if TRUE, sort by decreasing importance.
...	further arguments passed to or from other methods.

Value

a named vector of importance measures.

Author(s)

N. Ellis, CSIRO, Cleveland, Australia. <[e-mail]>. S.J. Smith, DFO, Dartmouth, NS, Canada. <[e-mail]>

See Also

importance.gradientForest

Examples

data(CoMLsimulation)
preds <- colnames(Xsimulation)
specs <- colnames(Ysimulation)
f1 <- gradientForest(data.frame(Ysimulation,Xsimulation), preds, specs[1:6], ntree=10)
f2 <- gradientForest(data.frame(Ysimulation,Xsimulation), preds, specs[1:6+6], ntree=10)
f12 <- combinedGradientForest(west=f1,east=f2)
importance(f12)
importance(f12, type = "Species", sort = FALSE)

gradientForest documentation built on Aug. 24, 2023, 3:03 p.m.